Object Detection for Dummies Part 3: R-CNN Family
This article is part three of a series on object detection for beginners. It focuses on the Region-Based Convolutional Neural Network (R-CNN) family, which includes models such as Fast R-CNN and Faster R-CNN. The author reviews the architecture and key components of these models, including region proposal networks and bounding box regression. The article also covers various techniques and tricks for improving performance in object detection tasks.
This article is part three of a series on object detection for beginners. It focuses on the Region-Based Convolutional Neural Network (R-CNN) family, which includes models such as Fast R-CNN and Faster R-CNN. The author reviews the architecture and key components of these models, including region proposal networks and bounding box regression. The article also covers various techniques and tricks for improving performance in object detection tasks.
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Why it matters: Understanding the R-CNN family is important for engineers working on computer vision projects that require accurate object detection. This knowledge can help them choose the right model architecture and implement efficient techniques to improve their project's performance.
Source: https://lilianweng.github.io/posts/2017-12-31-object-recognition-part-3/
This article was originally published at: https://lilianweng.github.io/posts/2017-12-31-object-reco...